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import sys
from fastchat.conversation import Conversation
from server.model_workers.base import *
from server.utils import get_httpx_client
from fastchat import conversation as conv
import json, httpx
from typing import List, Dict
from configs import logger, log_verbose
class GeminiWorker(ApiModelWorker):
def __init__(
self,
*,
controller_addr: str = None,
worker_addr: str = None,
model_names: List[str] = ["gemini-api"],
**kwargs,
):
kwargs.update(model_names=model_names, controller_addr=controller_addr, worker_addr=worker_addr)
kwargs.setdefault("context_len", 4096)
super().__init__(**kwargs)
def create_gemini_messages(self, messages) -> json:
has_history = any(msg['role'] == 'assistant' for msg in messages)
gemini_msg = []
for msg in messages:
role = msg['role']
content = msg['content']
if role == 'system':
continue
if has_history:
if role == 'assistant':
role = "model"
transformed_msg = {"role": role, "parts": [{"text": content}]}
else:
if role == 'user':
transformed_msg = {"parts": [{"text": content}]}
gemini_msg.append(transformed_msg)
msg = dict(contents=gemini_msg)
return msg
def do_chat(self, params: ApiChatParams) -> Dict:
params.load_config(self.model_names[0])
data = self.create_gemini_messages(messages=params.messages)
generationConfig = dict(
temperature=params.temperature,
topK=1,
topP=1,
maxOutputTokens=4096,
stopSequences=[]
)
data['generationConfig'] = generationConfig
url = "https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:generateContent" + '?key=' + params.api_key
headers = {
'Content-Type': 'application/json',
}
if log_verbose:
logger.info(f'{self.__class__.__name__}:url: {url}')
logger.info(f'{self.__class__.__name__}:headers: {headers}')
logger.info(f'{self.__class__.__name__}:data: {data}')
text = ""
json_string = ""
timeout = httpx.Timeout(60.0)
client = get_httpx_client(timeout=timeout)
with client.stream("POST", url, headers=headers, json=data) as response:
for line in response.iter_lines():
line = line.strip()
if not line or "[DONE]" in line:
continue
json_string += line
try:
resp = json.loads(json_string)
if 'candidates' in resp:
for candidate in resp['candidates']:
content = candidate.get('content', {})
parts = content.get('parts', [])
for part in parts:
if 'text' in part:
text += part['text']
yield {
"error_code": 0,
"text": text
}
print(text)
except json.JSONDecodeError as e:
print("Failed to decode JSON:", e)
print("Invalid JSON string:", json_string)
def get_embeddings(self, params):
print("embedding")
print(params)
def make_conv_template(self, conv_template: str = None, model_path: str = None) -> Conversation:
return conv.Conversation(
name=self.model_names[0],
system_message="You are a helpful, respectful and honest assistant.",
messages=[],
roles=["user", "assistant"],
sep="\n### ",
stop_str="###",
)
if __name__ == "__main__":
import uvicorn
from server.utils import MakeFastAPIOffline
from fastchat.serve.base_model_worker import app
worker = GeminiWorker(
controller_addr="http://127.0.0.1:20001",
worker_addr="http://127.0.0.1:21012",
)
sys.modules["fastchat.serve.model_worker"].worker = worker
MakeFastAPIOffline(app)
uvicorn.run(app, port=21012)
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